renaissance-movie-lens_0
[2025-06-11T22:56:54.994Z] Running test renaissance-movie-lens_0 ...
[2025-06-11T22:56:54.994Z] ===============================================
[2025-06-11T22:56:54.994Z] renaissance-movie-lens_0 Start Time: Wed Jun 11 22:56:54 2025 Epoch Time (ms): 1749682614723
[2025-06-11T22:56:54.994Z] variation: NoOptions
[2025-06-11T22:56:54.994Z] JVM_OPTIONS:
[2025-06-11T22:56:54.994Z] { \
[2025-06-11T22:56:54.994Z] echo ""; echo "TEST SETUP:"; \
[2025-06-11T22:56:54.994Z] echo "Nothing to be done for setup."; \
[2025-06-11T22:56:54.994Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17496826129933/renaissance-movie-lens_0"; \
[2025-06-11T22:56:54.994Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17496826129933/renaissance-movie-lens_0"; \
[2025-06-11T22:56:54.994Z] echo ""; echo "TESTING:"; \
[2025-06-11T22:56:54.994Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17496826129933/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-06-11T22:56:54.994Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17496826129933/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-06-11T22:56:54.994Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-06-11T22:56:54.994Z] echo "Nothing to be done for teardown."; \
[2025-06-11T22:56:54.994Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17496826129933/TestTargetResult";
[2025-06-11T22:56:54.994Z]
[2025-06-11T22:56:54.994Z] TEST SETUP:
[2025-06-11T22:56:54.994Z] Nothing to be done for setup.
[2025-06-11T22:56:54.994Z]
[2025-06-11T22:56:54.994Z] TESTING:
[2025-06-11T22:57:08.891Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2025-06-11T22:57:26.075Z] 22:57:25.395 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB.
[2025-06-11T22:57:29.532Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-06-11T22:57:30.174Z] Training: 60056, validation: 20285, test: 19854
[2025-06-11T22:57:30.174Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-06-11T22:57:30.903Z] GC before operation: completed in 406.457 ms, heap usage 229.019 MB -> 75.910 MB.
[2025-06-11T22:57:58.423Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T22:58:13.647Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T22:58:25.384Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T22:58:35.056Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T22:58:44.210Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T22:58:48.371Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T22:58:54.699Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T22:58:58.840Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T22:58:59.498Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-11T22:59:00.248Z] The best model improves the baseline by 14.34%.
[2025-06-11T22:59:00.248Z] Top recommended movies for user id 72:
[2025-06-11T22:59:00.248Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-11T22:59:00.248Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-11T22:59:00.248Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-11T22:59:00.248Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-11T22:59:00.248Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-11T22:59:00.248Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (89786.556 ms) ======
[2025-06-11T22:59:00.248Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-06-11T22:59:00.990Z] GC before operation: completed in 558.131 ms, heap usage 214.652 MB -> 91.430 MB.
[2025-06-11T22:59:08.749Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T22:59:18.156Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T22:59:24.645Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T22:59:32.919Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T22:59:36.103Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T22:59:39.616Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T22:59:47.769Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T22:59:51.955Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T22:59:53.438Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-11T22:59:53.438Z] The best model improves the baseline by 14.34%.
[2025-06-11T22:59:53.438Z] Top recommended movies for user id 72:
[2025-06-11T22:59:53.438Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-11T22:59:53.438Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-11T22:59:53.438Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-11T22:59:53.438Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-11T22:59:53.438Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-11T22:59:53.438Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (52632.953 ms) ======
[2025-06-11T22:59:53.438Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-06-11T22:59:54.127Z] GC before operation: completed in 294.484 ms, heap usage 140.396 MB -> 87.799 MB.
[2025-06-11T23:00:01.858Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:00:09.831Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:00:17.727Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:00:24.471Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:00:31.198Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:00:38.431Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:00:42.858Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:00:48.113Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:00:48.113Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-11T23:00:48.113Z] The best model improves the baseline by 14.34%.
[2025-06-11T23:00:48.837Z] Top recommended movies for user id 72:
[2025-06-11T23:00:48.837Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-11T23:00:48.837Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-11T23:00:48.837Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-11T23:00:48.837Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-11T23:00:48.837Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-11T23:00:48.837Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (54882.850 ms) ======
[2025-06-11T23:00:48.837Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-06-11T23:00:48.837Z] GC before operation: completed in 454.453 ms, heap usage 186.865 MB -> 88.468 MB.
[2025-06-11T23:00:55.423Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:01:12.378Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:01:19.192Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:01:29.274Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:01:35.170Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:01:38.523Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:01:44.785Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:01:52.158Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:01:52.158Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-11T23:01:52.158Z] The best model improves the baseline by 14.34%.
[2025-06-11T23:01:52.920Z] Top recommended movies for user id 72:
[2025-06-11T23:01:52.920Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-11T23:01:52.920Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-11T23:01:52.920Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-11T23:01:52.920Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-11T23:01:52.920Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-11T23:01:52.920Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (63453.016 ms) ======
[2025-06-11T23:01:52.920Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-06-11T23:01:52.920Z] GC before operation: completed in 611.848 ms, heap usage 141.152 MB -> 88.731 MB.
[2025-06-11T23:02:02.227Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:02:07.306Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:02:15.051Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:02:21.239Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:02:26.901Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:02:32.953Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:02:36.132Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:02:40.199Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:02:40.881Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-11T23:02:40.881Z] The best model improves the baseline by 14.34%.
[2025-06-11T23:02:41.588Z] Top recommended movies for user id 72:
[2025-06-11T23:02:41.588Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-11T23:02:41.588Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-11T23:02:41.588Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-11T23:02:41.588Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-11T23:02:41.588Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-11T23:02:41.588Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (48089.350 ms) ======
[2025-06-11T23:02:41.588Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-06-11T23:02:41.588Z] GC before operation: completed in 392.089 ms, heap usage 233.662 MB -> 88.787 MB.
[2025-06-11T23:02:51.317Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:02:59.354Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:03:04.498Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:03:09.776Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:03:14.975Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:03:19.235Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:03:24.403Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:03:28.664Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:03:28.664Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-11T23:03:28.664Z] The best model improves the baseline by 14.34%.
[2025-06-11T23:03:29.412Z] Top recommended movies for user id 72:
[2025-06-11T23:03:29.412Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-11T23:03:29.412Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-11T23:03:29.412Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-11T23:03:29.412Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-11T23:03:29.412Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-11T23:03:29.412Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (47471.783 ms) ======
[2025-06-11T23:03:29.412Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-06-11T23:03:29.412Z] GC before operation: completed in 290.459 ms, heap usage 166.145 MB -> 89.037 MB.
[2025-06-11T23:03:35.676Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:03:43.480Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:03:51.745Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:03:59.670Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:04:03.695Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:04:07.903Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:04:14.018Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:04:17.065Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:04:18.402Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-11T23:04:18.402Z] The best model improves the baseline by 14.34%.
[2025-06-11T23:04:18.402Z] Top recommended movies for user id 72:
[2025-06-11T23:04:18.402Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-11T23:04:18.402Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-11T23:04:18.402Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-11T23:04:18.402Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-11T23:04:18.402Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-11T23:04:18.402Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (48638.336 ms) ======
[2025-06-11T23:04:18.402Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-06-11T23:04:18.402Z] GC before operation: completed in 513.052 ms, heap usage 108.498 MB -> 88.854 MB.
[2025-06-11T23:04:24.819Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:04:30.304Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:04:35.328Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:04:40.319Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:04:43.351Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:04:47.748Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:04:53.025Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:04:56.057Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:04:56.742Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-11T23:04:56.742Z] The best model improves the baseline by 14.34%.
[2025-06-11T23:04:56.742Z] Top recommended movies for user id 72:
[2025-06-11T23:04:56.742Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-11T23:04:56.742Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-11T23:04:56.742Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-11T23:04:56.742Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-11T23:04:56.742Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-11T23:04:56.742Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (38351.904 ms) ======
[2025-06-11T23:04:56.742Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-06-11T23:04:57.403Z] GC before operation: completed in 311.930 ms, heap usage 356.610 MB -> 89.546 MB.
[2025-06-11T23:05:03.742Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:05:11.608Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:05:21.472Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:05:29.228Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:05:31.663Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:05:35.966Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:05:39.098Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:05:43.579Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:05:43.579Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-11T23:05:43.579Z] The best model improves the baseline by 14.34%.
[2025-06-11T23:05:44.252Z] Top recommended movies for user id 72:
[2025-06-11T23:05:44.252Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-11T23:05:44.252Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-11T23:05:44.252Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-11T23:05:44.252Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-11T23:05:44.252Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-11T23:05:44.252Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (46772.226 ms) ======
[2025-06-11T23:05:44.252Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-06-11T23:05:44.252Z] GC before operation: completed in 255.682 ms, heap usage 206.068 MB -> 89.213 MB.
[2025-06-11T23:05:50.579Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:05:56.915Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:06:02.290Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:06:09.539Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:06:11.726Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:06:15.238Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:06:22.187Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:06:23.581Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:06:24.368Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-11T23:06:24.368Z] The best model improves the baseline by 14.34%.
[2025-06-11T23:06:25.140Z] Top recommended movies for user id 72:
[2025-06-11T23:06:25.140Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-11T23:06:25.140Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-11T23:06:25.140Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-11T23:06:25.140Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-11T23:06:25.140Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-11T23:06:25.140Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (40562.539 ms) ======
[2025-06-11T23:06:25.140Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-06-11T23:06:25.140Z] GC before operation: completed in 259.796 ms, heap usage 188.927 MB -> 89.299 MB.
[2025-06-11T23:06:33.267Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:06:41.484Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:06:47.904Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:06:55.775Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:06:58.820Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:07:03.455Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:07:07.653Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:07:10.713Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:07:10.713Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-11T23:07:10.713Z] The best model improves the baseline by 14.34%.
[2025-06-11T23:07:11.373Z] Top recommended movies for user id 72:
[2025-06-11T23:07:11.373Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-11T23:07:11.373Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-11T23:07:11.373Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-11T23:07:11.373Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-11T23:07:11.373Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-11T23:07:11.373Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (46090.009 ms) ======
[2025-06-11T23:07:11.373Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-06-11T23:07:11.373Z] GC before operation: completed in 299.958 ms, heap usage 209.423 MB -> 89.040 MB.
[2025-06-11T23:07:19.834Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:07:22.831Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:07:29.362Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:07:35.655Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:07:37.853Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:07:40.942Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:07:45.325Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:07:49.402Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:07:49.402Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-11T23:07:49.402Z] The best model improves the baseline by 14.34%.
[2025-06-11T23:07:49.402Z] Top recommended movies for user id 72:
[2025-06-11T23:07:49.402Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-11T23:07:49.402Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-11T23:07:49.402Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-11T23:07:49.402Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-11T23:07:49.402Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-11T23:07:49.402Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (37976.930 ms) ======
[2025-06-11T23:07:49.402Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-06-11T23:07:50.065Z] GC before operation: completed in 707.685 ms, heap usage 396.967 MB -> 89.628 MB.
[2025-06-11T23:07:55.155Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:07:59.064Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:08:02.989Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:08:07.217Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:08:10.406Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:08:14.560Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:08:21.856Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:08:24.898Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:08:25.589Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-11T23:08:25.589Z] The best model improves the baseline by 14.34%.
[2025-06-11T23:08:25.589Z] Top recommended movies for user id 72:
[2025-06-11T23:08:25.589Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-11T23:08:25.589Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-11T23:08:25.589Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-11T23:08:25.589Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-11T23:08:25.589Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-11T23:08:25.589Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (35607.820 ms) ======
[2025-06-11T23:08:25.589Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-06-11T23:08:26.274Z] GC before operation: completed in 248.831 ms, heap usage 204.614 MB -> 89.364 MB.
[2025-06-11T23:08:31.437Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:08:36.707Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:08:44.782Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:08:51.421Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:08:54.501Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:08:58.653Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:09:01.688Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:09:04.877Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:09:05.588Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-11T23:09:05.588Z] The best model improves the baseline by 14.34%.
[2025-06-11T23:09:05.588Z] Top recommended movies for user id 72:
[2025-06-11T23:09:05.588Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-11T23:09:05.588Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-11T23:09:05.588Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-11T23:09:05.588Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-11T23:09:05.588Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-11T23:09:05.588Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (39471.575 ms) ======
[2025-06-11T23:09:05.588Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-06-11T23:09:06.414Z] GC before operation: completed in 457.911 ms, heap usage 236.455 MB -> 89.207 MB.
[2025-06-11T23:09:11.665Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:09:16.920Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:09:23.148Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:09:28.235Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:09:32.400Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:09:37.029Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:09:41.064Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:09:47.693Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:09:47.693Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-11T23:09:47.693Z] The best model improves the baseline by 14.34%.
[2025-06-11T23:09:47.693Z] Top recommended movies for user id 72:
[2025-06-11T23:09:47.693Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-11T23:09:47.693Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-11T23:09:47.693Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-11T23:09:47.693Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-11T23:09:47.693Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-11T23:09:47.693Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (41648.629 ms) ======
[2025-06-11T23:09:47.693Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-06-11T23:09:48.498Z] GC before operation: completed in 454.212 ms, heap usage 304.610 MB -> 89.617 MB.
[2025-06-11T23:09:56.318Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:10:01.253Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:10:09.001Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:10:15.494Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:10:19.685Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:10:24.020Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:10:30.609Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:10:32.865Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:10:34.342Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-11T23:10:34.342Z] The best model improves the baseline by 14.34%.
[2025-06-11T23:10:34.342Z] Top recommended movies for user id 72:
[2025-06-11T23:10:34.342Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-11T23:10:34.342Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-11T23:10:34.342Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-11T23:10:34.342Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-11T23:10:34.342Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-11T23:10:34.342Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (46520.270 ms) ======
[2025-06-11T23:10:34.342Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-06-11T23:10:35.101Z] GC before operation: completed in 240.569 ms, heap usage 214.759 MB -> 89.311 MB.
[2025-06-11T23:10:41.699Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:10:53.685Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:11:00.631Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:11:04.599Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:11:11.537Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:11:17.292Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:11:29.500Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:11:36.012Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:11:36.012Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-11T23:11:36.012Z] The best model improves the baseline by 14.34%.
[2025-06-11T23:11:36.679Z] Top recommended movies for user id 72:
[2025-06-11T23:11:36.679Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-11T23:11:36.679Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-11T23:11:36.679Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-11T23:11:36.679Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-11T23:11:36.679Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-11T23:11:36.679Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (61605.419 ms) ======
[2025-06-11T23:11:36.679Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-06-11T23:11:36.679Z] GC before operation: completed in 305.542 ms, heap usage 177.843 MB -> 89.239 MB.
[2025-06-11T23:11:44.838Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:11:56.903Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:12:10.228Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:12:22.485Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:12:31.902Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:12:35.616Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:12:40.050Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:12:44.166Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:12:44.986Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-11T23:12:44.986Z] The best model improves the baseline by 14.34%.
[2025-06-11T23:12:45.683Z] Top recommended movies for user id 72:
[2025-06-11T23:12:45.683Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-11T23:12:45.683Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-11T23:12:45.683Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-11T23:12:45.683Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-11T23:12:45.683Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-11T23:12:45.683Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (68793.076 ms) ======
[2025-06-11T23:12:45.683Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-06-11T23:12:46.367Z] GC before operation: completed in 606.660 ms, heap usage 207.977 MB -> 85.870 MB.
[2025-06-11T23:12:54.469Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:13:01.468Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:13:07.822Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:13:14.842Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:13:17.109Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:13:21.199Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:13:24.298Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:13:28.668Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:13:29.375Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-11T23:13:29.375Z] The best model improves the baseline by 14.34%.
[2025-06-11T23:13:29.375Z] Top recommended movies for user id 72:
[2025-06-11T23:13:29.375Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-11T23:13:29.375Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-11T23:13:29.375Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-11T23:13:29.375Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-11T23:13:29.375Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-11T23:13:29.375Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (43413.770 ms) ======
[2025-06-11T23:13:29.375Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-06-11T23:13:30.117Z] GC before operation: completed in 509.004 ms, heap usage 209.824 MB -> 86.013 MB.
[2025-06-11T23:13:37.908Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T23:13:42.048Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T23:13:50.348Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T23:13:54.354Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T23:13:58.888Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T23:14:04.459Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T23:14:13.048Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T23:14:16.313Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T23:14:17.149Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-11T23:14:17.149Z] The best model improves the baseline by 14.34%.
[2025-06-11T23:14:17.149Z] Top recommended movies for user id 72:
[2025-06-11T23:14:17.149Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-11T23:14:17.149Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-11T23:14:17.149Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-11T23:14:17.149Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-11T23:14:17.149Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-11T23:14:17.149Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (46966.113 ms) ======
[2025-06-11T23:14:19.331Z] -----------------------------------
[2025-06-11T23:14:19.331Z] renaissance-movie-lens_0_PASSED
[2025-06-11T23:14:19.331Z] -----------------------------------
[2025-06-11T23:14:19.331Z]
[2025-06-11T23:14:19.331Z] TEST TEARDOWN:
[2025-06-11T23:14:19.331Z] Nothing to be done for teardown.
[2025-06-11T23:14:19.331Z] renaissance-movie-lens_0 Finish Time: Wed Jun 11 23:14:18 2025 Epoch Time (ms): 1749683658513